In the field of the digital interpretation of images associating the presence of shadows and light, two development directions can be seen. The first relates to the detection, and more especially, object identification in an image despite the presence of shadows. The second aims, more especially, to identify and interpret the shadow zones of an image, independently of the objects.
The first development direction is based on the assumption that an object can be recognized by its color, independently of whether or not this object is shadowed. The methods developed on the basis of this visual assessment are not always satisfactory, especially when there are significant image illumination contrasts.
The second development direction is more in line with an object of the invention that includes identifying the shadows in an image.
One well-known approach involves identifying in an image, the limits of an object bordered by a dark zone contrasting with the color of the object. However, this method enables identification of only a part of the shadow zones, as cast or relative shadows in this case, which are the projections of shadows on the surface of a body. In general, a cast or relative shadow, mentioned above, is distinguished from a “proper” shadow, the latter corresponding to the shadow of a body projected into space and visible for an observer on this same body. The distinction can be illustrated by the shadow of a person facing the dawn, which projects a cast or relative shadow behind his back, for example on the ground surface, but where the back itself also constitutes a “proper” shadow zone.
Another well-known approach is based on the spectral and structural characteristics of shadows, i.e. their colors and shapes. This approach enables the identification equally of cast shadows and proper shadows. It includes the digital segmentation of the image into finite color elements, from which is carried out an analysis of the radiation emitted by the image objects. One of the disadvantages of this technique is the fact that it is based on the structural characteristics of shadows, and that it requires digital segmentation of the image. In particular this means, using long and complex image processing, which requires improved calculation means and which does not always produce satisfactory results.
Therefore, there is a need to improve the quality of digital processing enabling the identification of the shadows in an image, and to achieve this using simple and rapid processes.